DocumentCode
2559798
Title
Unscented Particle Filter algorithm based on artificial fish swarm algorithm
Author
Tian, Yu-min ; Chen, Li
Author_Institution
Res. Inst. of Comput. Peripherals, Xidian Univ., Xi´´an, China
fYear
2012
fDate
29-31 May 2012
Firstpage
1123
Lastpage
1126
Abstract
Aiming at the problem of Unscented Particle Filter (UPF) algorithm such as particles degeneracy and particles impoverishment, by use of the behaviors of preying, swarming and following in the artificial fish swarm algorithm, an artificial fish swarm algorithm is used to make the particles of UKF move toward the global optimum, which optimalizes the resampling process and relieves the problem of particles degeneracy and impoverishment. Experiments show that this algorithm improves the estimation accuracy of UPF algorithm.
Keywords
Kalman filters; particle filtering (numerical methods); particle swarm optimisation; UKF; artificial fish swarm algorithm; particles degeneracy; particles impoverishment; preying behavior; resampling process optimisation; swarming behavior; unscented Kalman filter; unscented particle filter algorithm; Algorithm design and analysis; Fellows; Filtering algorithms; Marine animals; Particle filters; Signal processing algorithms; Artificial Fish Swarm Algorithm; Unscented Particle Filter; particles impoverishment; resampling;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation (ICNC), 2012 Eighth International Conference on
Conference_Location
Chongqing
ISSN
2157-9555
Print_ISBN
978-1-4577-2130-4
Type
conf
DOI
10.1109/ICNC.2012.6234707
Filename
6234707
Link To Document